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<section id="welcome-to-beyondml-s-documentation">
<h1>Welcome to BeyondML’s documentation!<a class="headerlink" href="#welcome-to-beyondml-s-documentation" title="Permalink to this heading"></a></h1>
<p>BeyondML is a Python package which enables creating sparse multitask artificial neural networks (MANNs)
compatible with <a class="reference external" href="https://tensorflow.org">TensorFlow</a> and <a class="reference external" href="https://pytorch.org">PyTorch</a>.
This package contains custom layers and utilities to facilitate the training and optimization of models
using the Reduction of Sub-Network Neuroplasticity (RSN2) training procedure developed by <a class="reference external" href="https://squared.ai">AI Squared, Inc</a>.</p>
<p><a class="reference download internal" download="" href="_downloads/24a622e4623b41fdb0fe92a5595144b2/beyondml.pdf"><code class="xref download docutils literal notranslate"><span class="pre">View</span> <span class="pre">this</span> <span class="pre">Documentation</span> <span class="pre">in</span> <span class="pre">PDF</span> <span class="pre">Format</span></code></a></p>
<section id="installation">
<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this heading"></a></h2>
<p>This package is available through <a class="reference external" href="https://pypi.org">Pypi</a> and can be installed by running the following command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">beyondml</span>
</pre></div>
</div>
<p>Alternatively, the latest version of the software can be installed directly from GitHub using the following command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">git</span><span class="o">+</span><span class="n">https</span><span class="p">:</span><span class="o">//</span><span class="n">github</span><span class="o">.</span><span class="n">com</span><span class="o">/</span><span class="n">beyond</span><span class="o">-</span><span class="n">ml</span><span class="o">-</span><span class="n">labs</span><span class="o">/</span><span class="n">beyondml</span>
</pre></div>
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<li class="toctree-l1"><a class="reference internal" href="modules.html">beyondml</a><ul>
<li class="toctree-l2"><a class="reference internal" href="beyondml.html">beyondml package</a></li>
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</section>
<section id="changelog">
<h2>Changelog<a class="headerlink" href="#changelog" title="Permalink to this heading"></a></h2>
<ul class="simple">
<li><dl class="simple">
<dt>Version 0.1.0</dt><dd><ul>
<li><p>Refactored existing MANN repository to rename to BeyondML</p></li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.1</dt><dd><ul>
<li><dl class="simple">
<dt>Added the <cite>SparseDense</cite>, <cite>SparseConv</cite>, <cite>SparseMultiDense</cite>, and <cite>SparseMultiConv</cite> layers to</dt><dd><p><cite>beyondml.tflow.layers</cite>, giving users the functionality to utilize sparse tensors during
inference</p>
</dd>
</dl>
</li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.2</dt><dd><ul>
<li><p>Added the <cite>MaskedMultiHeadAttention</cite>, <cite>MaskedTransformerEncoderLayer</cite>, and <cite>MaskedTransformerDecoderLayer</cite> layers to <cite>beyondml.pt.layers</cite> to add pruning to the transformer architecture</p></li>
<li><p>Added <cite>MaskedConv3D</cite>, <cite>MultiMaskedConv3D</cite>, <cite>MultiConv3D</cite>, <cite>MultiMaxPool3D</cite>, <cite>SparseConv3D</cite>, and <cite>SparseMultiConv3D</cite> layers to <cite>beyondml.tflow.layers</cite></p></li>
<li><p>Added <cite>MaskedConv3D</cite>, <cite>MultiMaskedConv3D</cite>, <cite>MultiConv3D</cite>, <cite>MultiMaxPool3D</cite>, <cite>SparseConv3D</cite>, <cite>SparseMultiConv3D</cite>, and <cite>MultiMaxPool2D</cite> layers to <cite>beyondml.pt.layers</cite></p></li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.3</dt><dd><ul>
<li><p>Added <cite>beyondml.pt</cite> compatibility with more native PyTorch functionality for using models on different devices and datatypes</p></li>
<li><p>Added <cite>train_model</cite> function to <cite>beyondml.tflow.utils</cite></p></li>
<li><p>Added <cite>MultitaskNormalization</cite> layer to <cite>beyondml.tflow.layers</cite> and <cite>beyondml.pt.layers</cite></p></li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.4</dt><dd><ul>
<li><p>Updated documentation to use Sphinx</p></li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.5</dt><dd><ul>
<li><p>Updated requirements to use newer version of TensorFlow</p></li>
<li><p>Fixed errors with changes to types of <cite>input_shape</cite> in TensorFlow Keras layers</p></li>
<li><p>Fixed errors resulting from model/configuration changes with TensorFlow</p></li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.6</dt><dd><ul>
<li><p>Fixed issues with converting between masked and unmasked models in TensorFlow</p></li>
</ul>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>Version 0.1.7</dt><dd><ul>
<li><p>Updated Pytorch implementation of Transformer-based architectures</p></li>
</ul>
</dd>
</dl>
</li>
</ul>
</section>
</section>


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